Machine Learning Engineer

Job Title: MLOps Engineer

Urgent — High Priority requirement.

1. Location - Hyderabad/ Pune

2. Interview Rounds - 4 round.

3. Contract - 12 Months

Only CVs shared to google form in this link https://lnkd.in/d6JKrF3E will be accepted.

About Client:

We are a fast-growing boutique data engineering firm that empowers enterprises to manage and harness their data landscape efficiently. Leveraging advanced machine learning (ML) methodologies,

Job Overview:

We are seeking a highly skilled and motivated MLOps Engineer with 3–5 years of experience to join our engineering team. The ideal candidate should possess a strong foundation in DevOps or software engineering principles with practical exposure to machine learning operational workflows. You will be instrumental in operationalizing ML systems, optimizing the deployment lifecycle, and strengthening the integration between data science and engineering teams.

Required Skills:

● Hands-on experience with MLOps platforms such as MLflow and Kubeflow.

● Proficiency in Infrastructure as Code (IaC) tools like Terraform or Ansible.

● Strong familiarity with monitoring and alerting frameworks (Prometheus, Grafana, Datadog, AWS CloudWatch).

● Solid understanding of microservices architecture, service discovery, and load balancing.

● Excellent programming skills in Python, with experience in writing modular, testable, and maintainable code.

● Proficient in Docker and container-based application deployments.

● Experience with CI/CD tools such as Jenkins or GitLab CI.

● Basic working knowledge of Kubernetes for container orchestration.

● Practical experience with cloud-based ML platforms such as AWS SageMaker, Databricks, or Google Vertex AI.

● Competency in Linux shell scripting and command-line operations.

● Proficiency with Git and version control best practices.

● Foundational knowledge of machine learning principles and typical ML workflow patterns.

Good-to-Have Skills:

● Awareness of security practices specific to ML pipelines, including secure model endpoints and data protection.

● Experience with scripting languages like Bash or PowerShell for automation tasks.

● Exposure to database scripting and data integration pipelines.

Experience & Qualifications:

● 3–5+ years of experience in MLOps, Site Reliability Engineering (SRE), or Software Engineering roles.

● At least 2+ years of hands-on experience working on ML/AI systems in production settings.

● Deep understanding of cloud-native architectures, containerization, and the end-to-end ML lifecycle.

● Bachelor’s degree in Computer Science, Software Engineering, or a related technical field.

● Relevant certifications such as AWS Certified DevOps Engineer – Professional are a strong plus.